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Internship Ai Infrastructure Engineer Jobs (NOW HIRING)

Gatik AI

Senior AI Infrastructure Engineer

Santa Clara, CA

$127K - $173K/yr

About the role We are seeking a Senior AI Infrastructure Engineer to design, build, and scale the high-performance AI platform powering our autonomous driving models. While researchers focus on ...

Gatik AI

Senior AI Infrastructure Engineer

Santa Clara, CA · On-site

$127K - $173K/yr

About the role We are seeking a Senior AI Infrastructure Engineer to design, build, and scale the high-performance AI platform powering our autonomous driving models. While researchers focus on ...

vCluster Labs

AI Infrastructure Engineer

New York, NY · Remote

$150K - $200K/yr

As an AI Infrastructure Engineer, your role will include: * Lead Technical Deployments: Drive end-to-end technical deployments for GPU neocloud and AI Factory customers, from initial bare metal ...

Scout Motors

AI Infrastructure Engineer

Charlotte, NC · On-site

$105K - $137K/yr

Deploy and manage AI services across cloud and on-prem environments. * Automate infrastructure ... Collaborate with engineering, data, and product teams to support AI initiatives. * Excellent ...

Scout Motors

AI Infrastructure Engineer

Charlotte, NC · On-site

$140K - $170K/yr

Deploy and manage AI services across cloud and on-prem environments. * Automate infrastructure ... Collaborate with engineering, data, and product teams to support AI initiatives. * Excellent ...

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$126K - $165K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$126K - $165K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$117K - $154K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

Spellbrush

AI Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Spellbrush, the world's leading generative AI studio behind niji・journey , is looking for an AI Infrastructure Engineer to join us in building out end-to-end ML infrastructure to run our models on ...

Spellbrush

AI Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Spellbrush, the world's leading generative AI studio behind niji・journey , is looking for an AI Infrastructure Engineer to join us in building out end-to-end ML infrastructure to run our models on ...

NIO USA, INC

AI Infrastructure Engineer

San Jose, CA · On-site

$192K - $249K/yr

About the Position We are looking for a senior AI Inference Infrastructure Software Engineer with strong hands-on experience building, optimizing, and deploying high-performance, scalable inference ...

Intel

AI Infrastructure Engineer

Hillsboro, OR

$170K - $315K/yr

We are looking for a performance-obsessed AI Infrastructure Engineer to push LLM inference to its absolute limits on Intel's next-generation GPU architectures. In this role, you will dive deep into ...

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Internship Ai Infrastructure Engineer information

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How much do internship ai infrastructure engineer jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for internship ai infrastructure engineer in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is the difference between Internship Ai Infrastructure Engineer vs Data Engineer?

AspectInternship Ai Infrastructure EngineerData Engineer
Required CredentialsEnrolled in or recent graduate of Computer Science, Engineering, or related fields; some knowledge of AI and infrastructure toolsBachelor's or higher in Computer Science, Data Science, or related; experience with databases and data pipelines
Work EnvironmentInternship setting, collaborative teams, learning-focusedFull-time, technical teams managing data systems and pipelines
Employer & Industry UsageTech companies, AI startups, research labsTech firms, finance, healthcare, and other data-driven industries

The Internship Ai Infrastructure Engineer role focuses on supporting AI infrastructure projects during an internship, emphasizing learning and assisting with AI systems setup. In contrast, Data Engineers build and maintain data pipelines and infrastructure for data analysis. While both roles require knowledge of technical tools, the internship role is more entry-level and learning-oriented, whereas Data Engineers are more experienced and responsible for ongoing data management.

What does an internship AI infrastructure engineer do?

An Internship AI Infrastructure Engineer assists in designing, developing, and maintaining the foundational systems that support artificial intelligence (AI) applications. They work with cloud platforms, data pipelines, and scalable computing resources to ensure that AI models can be trained and deployed efficiently. Interns may help automate workflows, optimize performance, and collaborate with data scientists and software engineers. The role provides hands-on experience with the tools and frameworks commonly used in AI engineering environments.

What are the key skills and qualifications needed to thrive as an internship AI infrastructure engineer, and why are they important?

To thrive as an Internship AI Infrastructure Engineer, you need a solid understanding of computer science fundamentals, programming (especially in Python or C++), and basic knowledge of machine learning frameworks, often supported by ongoing studies in a relevant field. Familiarity with cloud platforms (like AWS, GCP, or Azure), version control systems (such as Git), and containerization tools (Docker, Kubernetes) is typically expected. Strong problem-solving abilities, curiosity, teamwork, and effective communication help interns stand out and integrate quickly into engineering teams. These skills are crucial for supporting scalable AI solutions, collaborating on complex projects, and contributing meaningfully in a fast-evolving technical environment.

What types of projects and responsibilities can an internship AI infrastructure engineer expect to work on?

As an AI Infrastructure Engineer intern, you can expect to be involved in projects that support the development, deployment, and scaling of AI models. Typical responsibilities may include optimizing data pipelines, maintaining and improving cloud or on-premise computing resources, and collaborating closely with data scientists to ensure efficient model training and inference. Interns often get hands-on experience with tools such as Docker, Kubernetes, and various cloud platforms, and work in cross-functional teams to troubleshoot and enhance AI workflows. This role provides a solid foundation in both software engineering and AI operations, preparing you for advanced positions in the field.
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Internship Ai Infrastructure Engineer jobs near you
Infographic showing various Internship Ai Infrastructure Engineer job openings in the United States as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.

AI Infrastructure Engineer (Forward Deployed AI Engineer)

WorkNovas LLC

Fort Mill, SC • On-site

$94K - $123K/yr

Contractor

Posted 6 days ago

Job description

AI Infrastructure Engineer (Forward Deployed AI Engineer)

Location: Fort Mill, SC (Onsite)

Job Summary: We are seeking a proactive and innovative AI Infrastructure Engineer to work directly with our LPL infrastructure teams. The ideal candidate will identify opportunities for automation, build AI-powered solutions, and enhance engineering productivity. This role requires a strong foundation in Python development, infrastructure engineering, and a deep understanding of GitHub tools.

 

Responsibilities:

  • Embed within infrastructure teams to understand workflows and identify automation opportunities.
  • Independently identify and implement automation solutions.
  • Build AI-assisted solutions utilizing Cursor and GitHub Copilot.
  • Develop infrastructure automation processes to streamline operations.
  • Create AI workflows and AI agents to enhance productivity.
  • Modernize existing infrastructure platforms for improved performance.
  • Enhance cloud migration efficiency through innovative solutions.
  • Automate vulnerability remediation processes.
  • Mentor existing engineering teams on best practices and AI adoption.
  • Promote AI adoption across the organization to drive efficiency.
  • Deliver measurable productivity improvements through automation.
  • Rapidly demonstrate proof-of-concepts to stakeholders.
  • Collaborate closely with business and infrastructure leaders to align on goals.

 

Mandatory Skills:

  • Strong proficiency in Python development.
  • Experience in infrastructure engineering.
  • Familiarity with cloud platforms, preferably AWS.
  • Expertise in Infrastructure as Code (IaC).
  • Proficient in GitHub Copilot and Cursor AI.
  • Knowledge of prompt engineering and LLM-based software development.
  • Experience with AI-assisted coding practices.
  • Strong understanding of DevOps principles and automation.
  • Proficient in APIs and scripting.
  • Excellent problem-solving skills and a self-starter mindset.
  • Strong communication skills to convey complex ideas effectively.

 

Preferred Skills:

  • Experience with agentic AI workflows and AI orchestration.
  • Knowledge of infrastructure modernization techniques.
  • Familiarity with security automation and vulnerability management.
  • Understanding of FinOps and observability practices.
  • Experience in platform engineering and cloud migration strategies.

 

Qualifications:

  • 3-5 years of relevant experience in AI infrastructure engineering.
  • Proven track record of delivering automation solutions that reduce manual effort.
  • Demonstrated ability to influence and mentor engineering teams.
  • Strong collaborative skills and ability to work in ambiguous environments.
  • Outcome-focused with a commitment to driving measurable improvements.

 

Success Measures:

  • Reduction of manual effort by 50-70% through automation.
  • Increased AI adoption across teams and projects.
  • Successful delivery of infrastructure automation initiatives.
  • Faster project execution and improved engineering productivity.
  • Positive influence on engineering culture and practices.

 

Desired Behavioral Traits:

  • AI-native mindset with a passion for innovation.
  • Highly proactive and curious about emerging technologies.
  • Independent thinker who can navigate ambiguity.
  • Strong collaborator with the ability to influence others.
  • Outcome-focused and committed to achieving results.